whisper-base-br
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6461
- eval_wer: 44.7778
- eval_cer: 17.8921
- eval_runtime: 465.9187
- eval_samples_per_second: 5.488
- eval_steps_per_second: 0.687
- epoch: 4.65
- step: 4000
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 6000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for gweltou/whisper-base-br
Base model
openai/whisper-base